#!/usr/bin/env python3
"""
AdvisorAI Data Pipeline Monitor - Gradio App
This is the main entry point for Hugging Face Spaces
"""

import gradio as gr
import json
import os
import sys
import logging
import time
from datetime import datetime

# Configure logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

def get_basic_health():
    """Get basic health status without external dependencies"""
    return {
        "status": "healthy",
        "timestamp": datetime.now().isoformat(),
        "message": "AdvisorAI Data Pipeline Monitor is running"
    }

def get_basic_pipeline_status():
    """Get basic pipeline status"""
    return {
        "status": "monitoring",
        "message": "Data pipeline monitoring active",
        "last_check": datetime.now().isoformat()
    }

def get_sample_data():
    """Get sample data for display"""
    return [
        ["sample_data.json", "merged/features/", "2.5 MB", "2025-01-18 10:30"],
        ["market_data.parquet", "alpaca/", "15.3 MB", "2025-01-18 10:25"],
        ["sentiment_data.json", "finviz/features/", "1.2 MB", "2025-01-18 10:20"]
    ]

def get_sample_logs():
    """Get sample log entries"""
    return """=== scheduler.log ===
2025-01-18 10:30:15 - INFO - Scheduler started successfully
2025-01-18 10:30:16 - INFO - Data collection task initiated
2025-01-18 10:30:45 - INFO - Market data fetched successfully

=== monitor.log ===
2025-01-18 10:30:00 - INFO - System monitoring active
2025-01-18 10:30:30 - INFO - Memory usage: 45%
2025-01-18 10:31:00 - INFO - All services running normally
"""

# Create Gradio interface
with gr.Blocks(title="AdvisorAI Data Pipeline Monitor", theme=gr.themes.Soft()) as app:
    gr.Markdown("# 🤖 AdvisorAI Data Pipeline Monitor")
    gr.Markdown("Real-time monitoring of the AdvisorAI data collection and processing pipeline")
    
    with gr.Tabs():
        with gr.TabItem("📊 Dashboard"):
            with gr.Row():
                with gr.Column():
                    gr.Markdown("### Health Status")
                    health_display = gr.JSON(label="System Health & Status")
                    
                with gr.Column():
                    gr.Markdown("### Pipeline Status")
                    pipeline_display = gr.JSON(label="Data Pipeline Status")
                    
            with gr.Row():
                refresh_btn = gr.Button("🔄 Refresh", variant="primary")
        
        with gr.TabItem("📁 Recent Files"):
            gr.Markdown("### Recently Modified Data Files")
            files_display = gr.Dataframe(
                headers=["File", "Path", "Size", "Modified"],
                value=get_sample_data(),
                label="Recent Files"
            )
            refresh_files_btn = gr.Button("🔄 Refresh Files")
        
        with gr.TabItem("📝 Logs"):
            gr.Markdown("### Recent Log Entries")
            logs_display = gr.Textbox(
                label="Recent Logs",
                value=get_sample_logs(),
                lines=15,
                max_lines=25,
                show_copy_button=True
            )
            refresh_logs_btn = gr.Button("🔄 Refresh Logs")
    
    # Event handlers
    def refresh_dashboard():
        health = get_basic_health()
        pipeline = get_basic_pipeline_status()
        return json.dumps(health, indent=2), json.dumps(pipeline, indent=2)
    
    def refresh_files():
        return get_sample_data()
    
    def refresh_logs():
        return get_sample_logs()
    
    # Connect event handlers
    refresh_btn.click(
        refresh_dashboard,
        outputs=[health_display, pipeline_display]
    )
    
    refresh_files_btn.click(
        refresh_files,
        outputs=[files_display]
    )
    
    refresh_logs_btn.click(
        refresh_logs,
        outputs=[logs_display]
    )
    
    # Auto-refresh on load
    app.load(
        refresh_dashboard,
        outputs=[health_display, pipeline_display]
    )

if __name__ == "__main__":
    logger.info("Starting Gradio app...")
    app.launch(
        server_name="0.0.0.0",
        server_port=7860,
        share=False,
        show_error=True
    )